A typical communications system can be modeled in terms of sending side 200 and a receiving side 400 with a channel 300 in between them. The sending side 200 usually consists of a data source 210 which generates data (bits) and a modulation system 220 which typically has a carrier which is modulated by the data and the output of the modulation system is band-limited using a Transmit Band Pass Filter (TBPF) 240. The output of the TBPF 240 is sent over a communications channel 300 to the receiving side 400. The channel 300 corrupts the transmitted signal with noise and any interference that might be exhibited due to the channel conditions. Also, the transmitted frequencies vary in frequency, phase and amplitude.
At the receiving side 200, the signal received from the channel 300 is passed through a Receive Band Pass Filter (RBPF) 410 that allows the modulated signal but limits the channel noise to the demodulator. The modulated signal is demodulated and passed through a matched filter 500 for data recovery. The impulse response of the matched filter 500 is trained with an initial signal without the channel noise for optimum waveform generation causing it to respond only to the specific transmitted signal on which it was trained. The demodulator output recovered with the band-limited channel noise is compared with the optimum waveforms generated to accurately estimate the data transmitted. As the number of waveforms increases due to the higher speed data operation, the noise immunity is reduced and therefore Bit Error Rates (BER) is increased. This limits the use of conventional matched filter that is optimized with known “expected waveforms” under no channel conditions as the data transfer rate is increased in bandwidth limited channel and thereby making it difficult to increase the data rates significantly. FIG. 1 shows a basic block diagram of a communications system.
Matched filters have been used for many years in communications channels to achieve optimized Bit Error Rate (BER) performance as a function of Energy per bit over Noise Density (Eb/N0). When the channel carries high-speed data, there is a degree of difficulty in conventional matched filters to characterize the channel condition in real time. One can use delayed characterization which is even more pronounced as the data transmission rate is significantly increased in a bandwidth limited channel. The noise immunity reduces to distinctly match the waveforms to recover the data at the receiver. Conventional matched filters which are trained under no noise condition tend to have more errors on high-speed data transmission as the noise immunity is reduced. As a result use of conventional matched filters cause ambiguities in data recovery and cause bit error rates to increase even when modest inter-frequency-interference is present. Therefore, the Eb/N0 has to be set higher for better Bit Error Rates.
An improved matched filter is desired that will characterize channel conditions in real time. An improved matched filter is needed that will increase the predictability of data even when data transmission rates are increased. A filter is further needed that achieves better data accuracy under channel noise condition when compared to conventional matched filters even when the noise immunity is reduced in high-speed data transmission. Further a communication system is desired that uses an improved matched filter that reduces real estate when compared to such conventional matched filters implemented at a receiver.